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在免疫保护之前对 SARS-CoV-2 呼吸道感染进行建模分析。

Modeling insights into SARS-CoV-2 respiratory tract infections prior to immune protection.

机构信息

Department of Mathematics, CSU Dominguez Hills, Carson, California.

Department of Mathematics, UNC Chapel Hill, Chapel Hill, North Carolina.

出版信息

Biophys J. 2022 May 3;121(9):1619-1631. doi: 10.1016/j.bpj.2022.04.003. Epub 2022 Apr 2.

Abstract

Mechanistic insights into human respiratory tract (RT) infections from SARS-CoV-2 can inform public awareness as well as guide medical prevention and treatment for COVID-19 disease. Yet the complexity of the RT and the inability to access diverse regions pose fundamental roadblocks to evaluation of potential mechanisms for the onset and progression of infection (and transmission). We present a model that incorporates detailed RT anatomy and physiology, including airway geometry, physical dimensions, thicknesses of airway surface liquids (ASLs), and mucus layer transport by cilia. The model further incorporates SARS-CoV-2 diffusivity in ASLs and best-known data for epithelial cell infection probabilities, and, once infected, duration of eclipse and replication phases, and replication rate of infectious virions. We apply this baseline model in the absence of immune protection to explore immediate, short-term outcomes from novel SARS-CoV-2 depositions onto the air-ASL interface. For each RT location, we compute probability to clear versus infect; per infected cell, we compute dynamics of viral load and cell infection. Results reveal that nasal infections are highly likely within 1-2 days from minimal exposure, and alveolar pneumonia occurs only if infectious virions are deposited directly into alveolar ducts and sacs, not via retrograde propagation to the deep lung. Furthermore, to infect just 1% of the 140 m of alveolar surface area within 1 week, either 10 boluses each with 10 infectious virions or 10 aerosols with one infectious virion, all physically separated, must be directly deposited. These results strongly suggest that COVID-19 disease occurs in stages: a nasal/upper RT infection, followed by self-transmission of infection to the deep lung. Two mechanisms of self-transmission are persistent aspiration of infected nasal boluses that drain to the deep lung and repeated rupture of nasal aerosols from infected mucosal membranes by speaking, singing, or cheering that are partially inhaled, exhaled, and re-inhaled, to the deep lung.

摘要

从 SARS-CoV-2 中获得的人类呼吸道 (RT) 感染的机制见解可以提高公众意识,并为 COVID-19 疾病的医疗预防和治疗提供指导。然而,RT 的复杂性以及无法访问不同区域,这给评估感染(和传播)发生和进展的潜在机制带来了根本障碍。我们提出了一个模型,该模型结合了详细的 RT 解剖结构和生理学,包括气道几何形状、物理尺寸、气道表面液体 (ASL) 的厚度以及纤毛对粘液层的输送。该模型进一步结合了 ASL 中的 SARS-CoV-2 扩散性以及上皮细胞感染概率的最佳已知数据,并且一旦被感染,就会经历隐伏期和复制期以及感染性病毒粒子的复制率。我们在没有免疫保护的情况下应用此基线模型来探索新型 SARS-CoV-2 在空气-ASL 界面上的新沉积对立即和短期结果的影响。对于每个 RT 位置,我们计算清除与感染的概率;对于每个被感染的细胞,我们计算病毒载量和细胞感染的动态。结果表明,从最小暴露后 1-2 天内,鼻感染的可能性非常高,并且只有当感染性病毒粒子直接沉积到肺泡导管和囊中时才会发生肺泡肺炎,而不是通过逆行传播到深部肺部。此外,要在 1 周内感染 140 米肺泡表面积的 1%,必须直接沉积 10 个每个含有 10 个感染性病毒粒子的 bolus 或 10 个含有 1 个感染性病毒粒子的气溶胶,且气溶胶之间均要物理隔离。这些结果强烈表明,COVID-19 疾病是分阶段发生的:鼻/上呼吸道 RT 感染,然后是感染向深部肺部的自我传播。自我传播有两种机制:感染的鼻 bolus 通过引流到深部肺部而持续被吸入,以及由于说话、唱歌或欢呼而导致感染的鼻气溶胶从感染的粘膜膜上反复破裂,这些气溶胶部分被吸入、呼出并再次吸入深部肺部。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10a8/9117927/e1d470b5e918/gr1.jpg

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